Daniel Beck | DeepAI

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Hao Li
205 publications
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79 publications
Lucia Specia
60 publications
Bill Byrne
40 publications
Stefan Winkler
34 publications
Javier Gonzalez
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David S. Leslie
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∙ 07/05/2023

PULSAR at MEDIQA-Sum 2023: Large Language Models Augmented by Synthetic Dialogue Convert Patient Dialogues to Medical Records

This paper describes PULSAR, our system submission at the ImageClef 2023...

0 Viktor Schlegel, et al. ∙

∙ 06/05/2023

PULSAR: Pre-training with Extracted Healthcare Terms for Summarising Patients' Problems and Data Augmentation with Black-box Large Language Models

Medical progress notes play a crucial role in documenting a patient's ho...

3 Hao Li, et al. ∙

∙ 10/17/2022

Modelling Emotion Dynamics in Song Lyrics with State Space Models

Most previous work in music emotion recognition assumes a single or a fe...

0 Yingjin Song, et al. ∙

∙ 08/12/2021

Generating Diverse Descriptions from Semantic Graphs

Text generation from semantic graphs is traditionally performed with det...

0 Jiuzhou Han, et al. ∙

∙ 10/02/2020

BOSS: Bayesian Optimization over String Spaces

This article develops a Bayesian optimization (BO) method which acts dir...

51 Henry B. Moss, et al. ∙

∙ 03/01/2019

A Unified Neural Architecture for Instrumental Audio Tasks

Within Music Information Retrieval (MIR), prominent tasks -- including p...

0 Steven Spratley, et al. ∙

∙ 06/26/2018

Graph-to-Sequence Learning using Gated Graph Neural Networks

Many NLP applications can be framed as a graph-to-sequence learning prob...

0 Daniel Beck, et al. ∙

∙ 06/30/2016

Exploring Prediction Uncertainty in Machine Translation Quality Estimation

Machine Translation Quality Estimation is a notoriously difficult task, ...

0 Daniel Beck, et al. ∙

∙ 04/18/2016

Speed-Constrained Tuning for Statistical Machine Translation Using Bayesian Optimization

We address the problem of automatically finding the parameters of a stat...

0 Daniel Beck, et al. ∙

∙ 08/10/2015

Learning Structural Kernels for Natural Language Processing

Structural kernels are a flexible learning paradigm that has been widely...

0 Daniel Beck, et al. ∙

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